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Data Scientist

Date: 18-Nov-2020

Location: Singapore, Singapore

Company: Singtel

Data Scientist - Job Description


The Role

Singtel Group Consumer has created an exciting new opportunity for a Data Scientist, who is passionate in delivering impact through analytics.
The successful candidate will design and build analytics solutions and products to deliver superior business outcomes, across all aspects of the business. Exceptional candidates will also show an analytical curiosity, going beyond the immediate requirements of the project to find deep insights that others have missed. 

Key Responsibilities

  • Translate pain-points of stakeholders into problem statements, architect and implement AI technologies/solutioning and present results and insights to business stakeholders.
  • Solid track record of deploying machine learning algorithms in production environment.
  • Develop and deploy analytical solutions across a variety of business functions, including, but not limited to: customer acquisition, customer retention, product development, pricing decisions, network roll-out
  • Track and improve performance of analytical solutions developed
  • Communicate findings to wider audiences within Singtel
  • Stay current on cutting edge business applications, tools and approaches

Required Skills and Qualifications

  • Strong stakeholder management
  • Significant relevant experience building and deploying advanced analytics solutions in telco, cable or B2C environment. Relevant topics include: customer acquisition, customer segmentation and targeting, customer LTV maximization, churn prevention, cost modeling of transportation & logistics operations, predictive maintenance
  • Advanced degree preferred: Masters degree with 3-5 years experience in computer science, applied mathematics, statistics, machine learning, or a related quantitative field.
  • Deep technical and data science expertise, including experience in the following:

          - Analytical methods: statistical modeling (e.g., linear regression, GLMs, time series), supervised machine learning (e.g., random forests, neural networks), design of experiments, segmentation/clustering, text mining, network analysis (e.g., location allocation), optimization, simulation
         -  Analytics tools: Data wrangling (SQL, R, Python, Spark, Hadoop/Hive, Impala), Data Modeling (R, Python), Data visualization (Tableau, Microstrategy)

  • Experience building in-production models, including associated scripting, error handling and documentation
  • Strong record of professional accomplishment 
  • Highly self-driven, demonstrate critical thinking, team player & fast learner
  • Excellent communication and presentation skills in English